Since the wide availability of computer systems of considerable computational speed, it has been possible to simulate the dynamics of vehicles (such as trains) in real time using computer software implemented models. As microprocessor systems have increased in speed and power at reduced cost, real time simulations can be hosted by relatively inexpensive desktop personal computer systems. Prior art vehicle driver support systems may be conveniently considered in a number of categories, including simple on-board driver advice systems, on-board vehicle control systems and remote vehicle control systems.
In the railway environment, on board driver advice systems typically utilize track and signal conditions to suggest control regimes to the driver of a rail vehicle for minimizing energy usage or provide other information about the position or performance of the train. A generic example of a prior art driver advice system, showing the typical functional aspects and interaction with a human driver, is illustrated in FIG. 1. Japanese Patent Document No. 58-075410 by Tokyo Shibaura Denki KK, describes a driving command device for providing guidance as to the optimum vehicle control settings in order to conserve energy. International Patent Application No PCT/AU89/00421 by Teknis Systems (Australia) Pty Ltd (& U.S. Pat. No. 5,239,472), describes a driver advice system for energy conservation on rail vehicles which monitors elapsed time and distance travelled for calculating the optimal coasting based on a predetermined arrival time. Most energy advisory systems available to date are focussed on suburban type trains, rather than long freight trains.
U.S. Pat. No. 5,740,547 to Kull discloses a railway navigation system that merely provides information defining the position of a railway vehicle on a track system to a driver via a position display. The article “On-board Train Management—LEADER proves its worth” by Hawthorn and Smith, Conference on Railway Engineering, 7-9 Sep. 1998 describes a locomotive driver assist display and event recorder system for predicting the future state of a train based on present throttle and brake inputs by the driver. These systems all rely on a driver's ability to interpret the advice provided and, based on personal experience and/or intuitively, to select future control settings. This relationship with the driver is illustrated in FIG. 2 of the accompanying drawings.
The second category of driver support systems are on-board vehicle control systems, that are typically driven by energy conservation and/or time-tabling concerns. One example is disclosed in U.S. Pat. No. 5,583,769 to Saitoh, assigned to Toshiba KK. This patent describes an automatic train operation apparatus that employs neural networks for controlling power and braking inputs in response to train speed information, a desired speed profile and signals from reference terminals for use in stopping the train at a desired position. U.S. Pat. No. 5,862,048 to Knight, assigned to New York Air Brake Corporation, describes a digitally controlled electro-pneumatic braking system that includes a train monitoring system for monitoring operating conditions of each vehicle by way of a specific type of computer network installed on the train.
The third type of driver support system are those which are located in a central office and communicate with one or more trains in a rail network. The article “Long haul fuel conservation system” by Milroy & Jerinc, Railway Engineering Conference, Adelaide 23-25 Sep. 1991, describes a central office dynamic rescheduling system for minimizing costs whilst satisfying operational requirements, including an on-board advice unit for generating tactical advice to the drivers of long haul trains based on certain journey (including track gradient) and train operating parameters. U.S. Pat. No. 5,332,180 to Peterson et al, assigned to Union Switch & Signal, describes a railway traffic control system wherein an inertial measurement apparatus is carried on a train for deriving a position estimate of the train for communication to central train control facility. The central control facility can include a dynamic track analyzer with a neural network which analyses position information from trains in order to calculate train rolling resistance. This information can be coordinated with acceleration data and a calculated braking strategy for the train in order to optimise fuel usage.
Some of the prior art systems, such as the Knight patent, provide information to the driver about train dynamics that have just occurred. This information, at least in the Knight patent, is obtained from step-wise numerical simulation using deterministic differential equations to provide certain train operational parameters without direct measurement. While such information may be useful, it does not provide any warning information to the driver that could be used to improve train stability in the immediate future, as may be achieved by effecting desirable control setting changes.
If undesirable or potentially dangerous train dynamics are to be minimized by driver intervention, then a system that gives advance warning of future train dynamics is required. The use of step-wise numerical integration to simulate future time is computationally prohibitive. To advance such a simulation just one step, using a typical step size of 10 ms, doubles the simulation computations because the existing real time simulation must be maintained. For a simulated advance warning system with a future prediction period of 60 seconds, the computational multiple is 6000. While such computational power may be available in mainframe installations or parallel processing facilities, they are not feasible for a vehicle on-board instrument of realistic cost.